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SUMMARY: Mass spectrometry (MS) methods are widely used for the analysis of biological and medical samples. Recently developed methods, such as DESI, REIMS and NESI allow fast analyses without sample preparation at the cost of higher variability of spectra. In biology and medicine, MS profiles are often used with machine learning (classification, regression, etc.) algorithms and statistical analysis, which are sensitive to outliers and intraclass variability. Here, we present spectra similarity matrix (SSM) Display software, a tool for fast visual outlier detection and variance estimation in mass spectrometric profiles. The tool speeds up the process of manual spectra inspection, improves accuracy and explainability of outlier detection, and decreases the requirements to the operator experience. It was shown that the batch effect could be revealed through SSM analysis and that the SSM calculation can also be used for tuning novel ion sources concerning the quality of obtained mass spectra. AVAILABILITY AND IMPLEMENTATION: Source code, example datasets, binaries and other information are available at https://github.com/EvgenyZhvansky/R_matrix. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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Complexes of peptide fragment 1-16 of beta-amyloid with transition metals play an important role in the development of a broad class of neurodegenerative diseases, which determines the interest in investigating the structures of these complexes. In this work, we have applied the method of the deuterium/hydrogen exchange in combination with ultra-high-resolution mass spectrometry to study conformational changes in (1-16) beta-amyloid peptide induced by binding of zinc(II) atoms. The efficiency of the deuterium/hydrogen exchange depended on the number of zinc atoms bound to the peptide and on the temperature of the ionization source region. Deuterium/hydrogen exchange reactions have been performed directly in the ionization source. The number of exchanges decreased considerably with an increasing numbers of zinc atoms. The relationship has been described with a damped exponential curve, which indicated that the binding of zinc atoms altered the conformation of the peptide ion by making it less open, which limits the access to inner areas of the molecule.
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Péptidos beta-Amiloides/química , Fragmentos de Péptidos/química , Acetato de Zinc/química , Medición de Intercambio de Deuterio , Modelos Moleculares , Unión Proteica , Estructura Secundaria de Proteína , Espectrometría de Masa por Ionización de Electrospray , TemperaturaRESUMEN
Significant metabolism alteration is accompanying the cell malignization process. Energy metabolism disturbance leads to the activation of de novo synthesis and beta-oxidation processes of lipids and fatty acids in a cancer cell, which becomes an indicator of pathological processes inside the cell. The majority of studies dealing with lipid metabolism alterations in glial tumors are performed using the cell lines in vitro or animal models. However, such conditions do not entirely represent the physiological conditions of cell growth or possible cells natural variability. This work presents the results of the data obtained by applying ambient mass spectrometry to human glioblastoma multiform tissues. By analyzing a relatively large cohort of primary and secondary glioblastoma samples, we identify the alterations in cells lipid composition, which accompanied the development of grade IV brain tumors. We demonstrate that primary glioblastomas, as well as ones developed from astrocytomas, are enriched with mono- and diunsaturated phosphatidylcholines (PC 26:1, 30:2, 32:1, 32:2, 34:1, 34:2). Simultaneously, the saturated and polyunsaturated phosphatidylcholines and phosphatidylethanolamines decrease. These alterations are obviously linked to the availability of the polyunsaturated fatty acids and activation of the de novo lipid synthesis and beta-oxidation pathways under the anaerobic conditions in the tumor core.
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Astrocitoma , Neoplasias Encefálicas , Glioblastoma , Animales , Humanos , Metabolismo de los Lípidos , FosfatidilcolinasRESUMEN
The majority of research in the biomedical sciences is carried out with the highest resolution accessible to the scientist, but, in the clinic, cost constraints necessitate the use of low-resolution devices. Here, we compare high- and low-resolution direct mass spectrometry profiling data and propose a simple pre-processing technique that makes high-resolution data suitable for the development of classification and regression techniques applicable to low-resolution data, while retaining high accuracy of analysis. This work demonstrates an approach to de-noising spectra to make the same representation for both high- and low-resolution spectra. This approach uses noise threshold detection based on the Tversky index, which compares spectra with different resolutions, and minimizes the percentage of resolution-specific peaks. The presented method provides an avenue for the development of analytical algorithms using high-resolution mass spectrometry data, while applying these algorithms in the clinic using low-resolution mass spectrometers.